Grant: Operating Grant

More than half cancer patients receive ionizing radiation as part of their treatment, and it remains as the main alternative once the disease is advanced. Radiation therapy is a localized treatment and requires accurate identification of the targeted area during planning and delivery.Advances in imaging technologies have allowed a new era of using imaging to guide and adapt radiation therapy to changes in disease anatomy. Recent years have witnessed increased interest in applying different imaging modalities to define the cancer region as well as enable estimation of the expected benefits versus risks of the designated treatment. It has been recognized that there is a noticeable value for using hybrid imaging in treatment planning, diagnosis, and staging of different cancer sites.In which complementary information from anatomical and functional images is combined to better characterize the cancer and predict response. Currently, this is manually considered based on only one physician's subjective expertise.This work, proposes a comprehensive framework for multimodality adaptive radiotherapy based on advanced image analysis and artificial intelligence methods. This will automate the integration of different imaging modalities features for accurate cancer definition, and prediction of outcomes, the design of optimal radiotherapy plans using so called 'dose painting' techniques. The project uses examples from two distinct cancer sites to demonstrate its versatility.This will then be used as an objective aid in treatment and adaptive planning for the patient to have better control of the disease, while maintaining the best quality of life possible for this individual patient.